An exemplary embodiment of this invention is in the field of 3-D interpretation, and more particularly to 3-D seismic interpretation. More specifically, an exemplary embodiment includes a workflow, including two new processes, implemented as software that is designed to enable automatic or semi-automatic interpretation of paleo-depositional features in three-dimensional seismic data for exploration, development and, for example, production of hydrocarbons.
The need for computer-aided, semi-automatic and automatic interpretation of depositional systems derives from a combination of factors. Energy resources are becoming steadily more difficult to find and develop. It has been recognized for many years that the majority of new oil and gas reserves are a function of a complex combination of geological, structural and stratigraphic elements. While the problems of exploration and the efficient development of hydrocarbon reserves have become more difficult, the volume of data to be interpreted for each project has become orders of magnitude greater over the past 20 years. Simultaneously, both the number of interpreters and the time allowed for interpretation have been substantially reduced. This drives the need for more advanced computer-aided processes that can support the interpreter by enabling more efficient, precise and effective interpretation of 3-D seismic data volumes.
Computer-aided structural interpretation of 3-D seismic data volumes has been embodied in tools in interactive seismic interpretation for a number of years. Since the early 1980s, horizon autotracking tools have been available to help increase the speed and consistency of horizon interpretation in 3-D seismic surveys (Dorn, 1998). More recently, techniques have been developed to provide computer-aided interpretation of faults and automatic fault interpretation (e.g., Crawford and Medwedeff, 1999, U.S. Pat. No. 5,987,388; Pederson, S. I., 2002, U.S. Pat. No. 7,203,342), as well as techniques beyond event autotracking to automatically interpret horizons (Dorn, 1999, U.S. Pat. No. 5,894,417; Stark, 1997, U.S. Pat. No. 5,671,344).
Computer tools to aid in stratigraphic interpretation of seismic volumes have developed much more slowly. Elements of depositional systems can most readily be identified by an interpreter when the morphology of the paleo-depositional system can be viewed. Similarly, it is most likely that a computer algorithm can be written to recognize, image, and extract elements of depositional systems if the computer algorithm is able to operate on the data in a domain where the paleo-depositional system's morphology is most readily imaged. In both of these cases, the optimal environment is the stratal-slice domain, where the slices through the volume of seismic data are close approximations of paleo-depositional surfaces.
In an undeformed data volume, horizontal slices (planar slices parallel to the (x,y) plane in the volume) may accurately represent depositional surfaces. However, in volumes with structural deformation, horizontal slices do not represent depositional surfaces for more than a small portion of the total volume. Faulting, folding, and velocity anomalies prevent the complete representation of such a surface by a simple horizontal slice.
Horizon-slicing is defined as creating a slice through a 3-D seismic volume in the shape of an interpreted seismic reflection in that volume. Horizon slicing (as opposed to horizontal slicing) has provided better images of depositional systems since the mid-to-late 1980s.
A continuous interval is a package of sediments that represent the same span of geologic age, but were deposited at different sedimentation rates in different parts of the volume. The result is an interval that represents that same amount of geologic time, but does not exhibit the same thickness. In such an interval, growth is caused by spatially variable rates of sedimentation. If we assume that sedimentation rates between a pair of bounding horizons are variable only in space (i.e., not vertically variable in a given location), stratal slices may be extracted by interpolating trace values vertically, where the interpolated sample interval at each (x,y) location is controlled by the upper and lower bounding surfaces and the number of samples desired in the interval on the output trace. This type of stratal slice has been referred to as a proportional slice.
Proportional slicing or stratal slicing developed in the mid 1990s (Posamentier, et. al., 1996; Zeng, et. al. 1998a, b, c) provides even better imaging of depositional systems, and better discrimination between stacked channel systems in the seismic data because these surfaces are typically a better approximation of paleo-depositional surfaces than either horizon slices or horizontal slices.
Zeng, et. al. (1998 a, b, c) describes the first instance of extracting slices based on geologic age. They reasoned that seismic reflectors do not always follow depositional surfaces. Thus, they interpolated seismic slices between surfaces judged to be time-equivalent. They referred to these interpolated slices as ‘stratal’ slices. Stark (2004) describes a similarly motivated effort. He used unwrapped phase as a proxy for user-interpreted age horizons. Slices were extracted from the data volume by drawing data from points of equal unwrapped phase. Stark's approach assumes that unwrapped phase closely approximates geologic age, but this is an assumption that is often in error.
Both horizon slicing and proportional slicing generally suffer from substantial limitations in that they do not accommodate and compensate for generalized 3-D structural deformation subsequent to deposition, nor do they properly account for the wide variety of depositional environments. Horizon slicing is only appropriate for a conformable sequence of horizons in the seismic volume (i.e., a spatially uniform depositional environment over time). Proportional slicing is only appropriate for an interval that exhibits growth (i.e., a spatially gradational change in depositional thickness over an area, often due to spatially differential subsidence). Horizon and proportional slicing do not properly reconstruct paleo-depositional surfaces in other depositional environments, nor do they account for post-depositional structural changes (particularly faulting) or post-depositional erosion.
Among the situations that the proportional or stratal slice volume (as defined by Zeng, et. al, 1998 a, b, c) does not handle properly are:                Angular unconformities        Non-linear growth in the interval between two horizons        Carbonate platform intervals        Faulting        
For example, both proportional slicing and stratal slicing (as defined by Zeng, et. al., 1998 a, b, c) produce volumes that have gaps or undefined zones where the volume is cut by a dipping fault surface. FIG. 1 shows, in a 2-D cross-section, the effects of dipping faults on this simple type of proportional slice for a pair of horizons. The output proportional slice volume is null or indeterminate at all (x,y) positions where one or both horizons is missing (e.g., Null Zone—1 Horizon in FIG. 1). The proportional slice volume is also indeterminate for (x,y) positions where both horizons are present but on opposite sides of a dipping fault surface (e.g., Null Zone—2 Horizons in FIG. 1).
The situation for more than one pair of horizons is shown in FIG. 2. In this case, there are null or indeterminate zones for each pair of horizons. These indeterminate zones are in different (x,y) positions for each pair of horizons.
In most previous attempts to solve this problem, where this simple form of proportional slicing is implemented, the indeterminate zones are filled with input seismic data rather than nulls, which can be quite misleading. Lomask et. al. (2006) have developed an approach that attempts to create a stratal volume without requiring interpreted horizons, faults or other surfaces to define and constrain the transformation. The lack of interpreted structural control in their approach produces poor results for seismic volumes that contain any significant structural deformation.
One exemplary embodiment of the Domain Transform method of this invention explicitly requires interpreted horizons, faults, and other geologic surfaces as input, and, as a result, does not suffer the limitations of the method proposed by Lomask.
Seismic-Wheeler Volumes (e.g., Stark, 2006) represent interpreted depositional systems tracts as well as hiatuses in deposition based on horizon interpretations of system boundaries in 3-D. This approach requires recognition of the system tract by the interpreter as a starting point, and does not take into account the effects of post-depositional structural deformation and faulting. The implementations of Seismic-Wheeler Volumes described by Stark (2006) also depend on association of each seismic sample in the volume with a relative geologic time (Stark, 2004; Stark 2005a, U.S. Pat. No. 6,850,845; Stark 2005b, U.S. Pat. No. 6,853,922). This constraint is not present in the process described here.
By transforming seismic data from the (x,y,time/depth) domain to the (x,y,stratal-slice) domain, data in a deformed volume can be interpreted in stratal-slice view. One exemplary goal is to reconstruct the data volume along stratal surfaces in an undeformed state using user-interpreted surfaces and user-supplied information on geologic relationships in the volume as a guide. Seismic data in this undeformed state is more easily and accurately interpreted for stratigraphy, depositional systems, and depositional environments.
Finally, a lightweight representation of volumetric data is often necessary for real-time rendering, for the segmentation of interpreted data, and for reducing visual clutter. A new Surface Wrapping technique has also been developed in accordance with an exemplary embodiment of this invention, and is described herein. For example, it allows, for example, the user to create a 3-D polygonal mesh that conforms to the exterior boundary of geobodies (such as stream channels) that offers significant improvements over existing techniques.
An inspiration for this Surface Wrapping approach was the Surface Draping algorithm (Dorn, 1999, U.S. Pat. No. 5,894,417), which allows a polygonal mesh to be defined that reflects the geometry of an interpreted horizon. The surface draping algorithm is based on the metaphor of laying an elastic sheet over a contoured surface: gravity pulls the sheet down, causing it to conform to the surface beneath it, and the tension of the elastic material allows the sheet to smoothly cover small gaps in the surface while preserving the important features.
Dorn's Surface Draping allows the user to view seismic data and define a series of points slightly above the desired horizon. These points define the initial shape of the 3-D mesh, which corresponds to the elastic sheet described above. When the user has completed this stage, the actual mesh is computed, generally using one vertex per voxel. These vertices are then iteratively “dropped” onto the horizon. At each step, the value of the voxel at each vertex's position is compared to a range that corresponds to the values found in an interpreted horizon. If the value falls within that range, the vertex is fixed in place.
The Surface Draping concept would have benefits if adapted to work on geobodies and other 3-D volumes. Other approaches have been used to define a mesh that surrounds and conforms to the shape of a volume. Acosta et. al. (2006a and b; U.S. Pat. Nos. 7,006,085 and 7,098,908) propose a technique where the bounding surface is defined slice-by-slice by a user as a set of spline curves or general polylines that are then connected in 3-D. Kobbelt et. al. (1999) describes a technique based on successive subdivision of an initially simple mesh that completely surrounds the volume. The technique described by Koo et. al. (2005) improves on the same idea by allowing the user to define an arbitrarily shaped grid around a point cloud, allowing holes in the volume to be interpreted properly. Both of the above algorithms work by moving each vertex to the nearest point in the volume.